Application of fluorescence spectroscopy in classifying apple juice according to the variety

Chemometrics-assisted excitation–emission matrix fluorescence spectroscopy for rapid identification of commercial reconstituted and sweetened grape juices

“…The reported methods for the identication of fruit juice include chromatography, mass spectrometry (MS), mid-infrared spectroscopy or uorescence spectroscopy, respectively, combined with chemometric methods. [16][17][18][19][20][21][22][23][24][25] Among them, chromatography, MS and their combined techniques have been frequently used, but these instruments are relatively expensive, and usually the sample pretreatment and operation are complicated and time-consuming during use. Ultraviolet visible (UV-vis) absorption spectroscopy, by contrast, is a simpler and less expensive alternative but provides a non-selective signal and less information.…”

Characterization and Classification of Direct and Commercial Strawberry Beverages Using Absorbance–Transmission and Fluorescence Excitation–Emission Matrix Technique

“…Many of the food components are fluorescent, and they contribute to the specific autofluorescence of products that may be used to evaluate various aspects of quality. Fluorescence was successfully used to evaluate various properties of fruit juices and extracts, including: apple [ 10 , 11 ], peach [ 12 ] plum [ 13 , 14 ], avocado [ 15 ], orange [ 16 ], and berry fruit [ 17 ]. In most of these studies, the fluorescence of the juices or extracts studied was associated with the presence of polyphenolic compounds.…”

Nondestructive estimation of three apple fruit properties at various ripening levels with optimal Vis-NIR spectral wavelength regression data

“…Among the widely used nondestructive methods for measuring fruit quality, Vis-NIR spectroscopy techniques are often the preferred ones (Pourdarbani et al, 2019). NIR spectroscopy applied to measure food quality has been presented by several researchers (Carames et al, 2017;Guo et al, 2016;Sirisomboon et al, 2018;Eisenstecken et al, 2016). Moreover, several investigations have been conducted to predict fruit quality.…”

“…In their study, mean error improved by 30% with the use of genetic algorithms. Bian et al (2021) studied the classification of apple juice based on variety and geographical origin. They applied PLS regression and fluorescent spectroscopy to analyze fluorescent spectra with two apple fruit varieties.…”

“…In their study, mean error improved by 30% with the use of genetic algorithms. Bian et al. (2021) studied the classification of apple juice based on variety and geographical origin.…”